1. Field of Invention
The present invention belongs to the field of information technologies, and relates to a decoding method, and specifically to a channel decoding method and decoder for tail-biting codes.
2. Description of Related Arts
In existing and next generation mobile communications networks, in order to ensure reliable transmission of data and control signaling, tail-biting convolutional codes, as highly efficient encoding scheme, are widely applied in various mobile communications systems. The tail-biting convolutional code is used in early IS-54, and current Enhanced Data Rate for GSM Evolution (EDGE), Worldwide Interoperability for Microwave Access (WiMax) and Long Term Evolution (LTE) systems. The tail-biting convolutional code is widely applied because the convolutional code encoded in a tail-biting manner eliminates the code rate loss caused by the known tail-bits that are used to initialize the encoder; meanwhile, a tail-biting structure provides all information bits with the same protection capability. Due to the above advantages, the tail-biting convolutional code is widely applied in various communications systems and serves as an encoding manner for control signaling. For short information sequence, encoding in tail-biting manner provides significant protection on code rate. For example, if an information sequence with cyclic redundancy check bits of total length of 40 bits in LTE broadcast channel is not encoded in tail-biting manner, the code rate loss reaches 13%. Currently, tail-biting convolutional codes have been used in EDGE, WiMax, LTE, and so on for control channel encoding.
Although the tail-biting convolutional code has a lot of advantages, implementation of an optimal decoding scheme based on the Viterbi algorithm is complex because a decoder knows neither the initial state nor the termination state of the encoder. Therefore, no optimal decoding scheme based on the Viterbi algorithm is available currently. A large quantity of current decoding algorithms, such as the Wrap-Around Viterbi Algorithm (WAVA) based on the circular Viterbi algorithm, are sub-optimal decoding algorithms. In order to find an optimal decoding algorithm for tail-biting convolutional codes, some scholars apply the shortest path search algorithm in the graph theory to the decoding algorithm of tail-biting convolutional codes, and obtain a two-step maximum likelihood decoding algorithm through designing a proper heuristic function. In the first step of the algorithm, the accumulated metrics of all surviving paths at each moment are obtained through a Modified Viterbi Algorithm (MVA). In the second step of the algorithm, an optimal tail-biting path output is obtained through a shortest path search algorithm. Such decoders use completely different search methods in the two steps, which is excessively complex for practical applications. Moreover, despite the partial reduction of the calculation amount, the heuristic search used in the algorithm requires a great number of push and pull operations as well as sequencing operations, and most importantly, the utilization ratio of a storage space is decreased. The space application is performed on the basis of the maximum storage space, leading to a low utilization ratio of a lot of storage spaces. Although search branches of such algorithm in Step 2 is significantly reduced as compared with the WAVA, the entire algorithm is performed in series since the search for a path corresponding to the minimum value of the current function f is performed under the instruction of the heuristic function, and an actual performing period is longer than that of two circles of the Viterbi algorithm.